Triple
T4705685
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Do Ho Suh |
E104386
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Do Ho Suh |
E104386
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Do Ho Suh | Statement: [Do Ho Suh, name, Do Ho Suh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Do Ho Suh Context triple: [Do Ho Suh, name, Do Ho Suh]
-
A.
Do Ho Suh
chosen
Do Ho Suh is a South Korean contemporary artist known for his intricate sculptures and installations that explore themes of home, memory, and personal space.
-
B.
Yong-taek Jung
Yong-taek Jung is a notable individual recognized for bearing the Korean surname Jung.
-
C.
Yong-gi Jung
Yong-gi Jung is a notable individual recognized as a prominent bearer of the Korean surname Jung.
-
D.
Ho-seok Jung
Ho-seok Jung is a notable individual recognized for achievements significant enough to be associated with the surname Jung.
-
E.
Jong Wook Kim
Jong Wook Kim is a machine learning researcher known for his contributions to multimodal models, including work on the development of CLIP at OpenAI.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69bd43eac3c08190af7e4020c6c3704c |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd63e808c88190877e98408498fb62 |
completed | March 20, 2026, 3:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be1067c6a081909fa06689ea66a8a4 |
completed | March 21, 2026, 3:28 a.m. |
Created at: March 20, 2026, 1:17 p.m.